Millennium
Website:
millenniumsys.com
Company:
https://www.linkedin.com/company/millennium-partners
Seniority: Not Applicable
Industries: Investment Management
Job details:
We are looking for a motivated
Quantitative Risk Modeler with
1- 3 years of experience to join our team. This role focuses on developing and maintaining multi-asset class analytics frameworks to the Firmwide portfolio of teams and senior management decision-making. If you have a passion for quantitative finance, risk modeling, and applied statistics, this is an excellent opportunity to grow your career in a dynamic and collaborative environment.
Principal Responsibilities
- Development of multi-asset class analytics across all MLP strategies, supporting the Office of the CIO across Enterprise-wide initiatives
- This includes working on the centralized performance evaluation framework at MLP, improvements on VaR and Stress methodologies, as well as implementing centralized back-testing and model performance frameworks
- Contributions to the development of multi-asset class content generation, as well as centralized visualization tools for the platform used by senior management.
- Ownership in developing a quantitative framework for identifying, measuring, managing, and reporting multi-asset class analytics across the platform.
- PM performance measurement and analytics to help inform management decisions.
- Ownership of a multi-asset class stress-testing framework, including insights into key risk drivers to action management decisions.
- Capital utilization and allocation models across portfolio manager teams. Cost of liquidation measurement and management, as well as associated returns relative to constrained resources.
- Post initial model development work, coordinate with relevant Technology departments to ensure changes are deployed into to production
Qualifications
- The candidate should have a degree in a quantitative field such as statistics, mathematics, computer science or financial engineering
- Strong programming skills, prior experience with Python (Polars and/or Pandas). Proficiency in at least a compiled and statically typed language is a plus
- Knowledge of mathematical and statistical analytics tools: estimation of linear models, dimensionality reduction techniques e.g. Equity Factor Models, Principal Component Analysis, and performance analytics (e.g., Sharpe ratios, drawdowns).
- Sense of responsibility and integrity. Intellectual curiosity and entrepreneurial mindset. Willingness to work and have fun in the process.
- Good presentation and communication skills, experience in either preparing or participating presentation for senior management-style meetings
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